No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by codexstar69 · Claude Skill · ★ 487
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is bug-hunter safe to install? View the security audit →
Bug Hunter AI code review that argues with itself — adversarial multi-agent bug finding, security scanning, and auto-fix for any coding agent. = 18" Install · Quick Start · How It Works · What It Finds · Auto-Fix · CLI Reference Bug Hunter is an open-source AI code review and security vulnerability scanner that works as a skill/plugin for AI coding agents. Three AI agents — a Hunter, a Skeptic, and a Referee — independently analyze your c
| Stars | 487 |
| Forks | 59 |
| Language | JavaScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 69.4820766251652/100 |
| Last Updated | 2026-08-17 |
| Created | 2026-03-07 |
| Platforms | claude-code, cli, codex, node, vscode |
| Est. Tokens | ~15k |
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bug-hunter is Adversarial AI bug hunter with auto-fix skill for Claude Code, Cursor, Codex CLI, GitHub Copilot CLI, Kiro CLI, Opencode, Pi Coding Agent, and more. Multi-agent pipeline finds security vulnerabilities. It is categorized as a Claude Skill with 487 GitHub stars.
bug-hunter is primarily written in JavaScript. It covers topics such as adversarial-ai, ai-code-review, auto-fix.
You can find installation instructions and usage details in the bug-hunter GitHub repository at github.com/codexstar69/bug-hunter. The project has 487 stars and 59 forks, indicating an active community.
bug-hunter is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to bug-hunter on Agent Skills Hub include agnix, multi-agent-ralph-loop, happier. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: